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The above areas can be classified into two broad categories from a business value perspective. Areas like Risk Management, Fraud Detection and Compliance are places where one needs to primarily play defense while realizing incremental value. Big Data, Analytics and Cloud Computing helps to gather a variety of data (both structured and unstructured) and then perform in memory or ‘on disk’ analysis of these feeds. The analysis can include plain MapReduce type processing or more sophisticated Data Science techniques. The result of such processing (standalone or combined with existing enterprise data) can be made available to analytical applications. This data can be incorporated as part of a business workflow which can allow LOB (Line Of Business) managers to track how effectively their teams are performing across different product lines. Cloud helps significantly in reducing the hardware/ software acquisition times as well as providing a high amount of hitherto lacking choice. Your applications and environments can now be truly polyglot in nature.
In the Trading arena across both latency sensitive and non latency sensitive applications, there is more and more demand to be able to incorporate social feeds into buy/sell decision– making without negatively impacting latency. We expect streaming real–time analytics projects (example. Impala, Stinger on Apache Hadoop or Apache Spark) to be developed further this year which will only reduce the speed and time to market in this area.










